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      <title>实现MySQL的横向扩展 - 交互式测验</title>
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          <div class="quiz-container">
            <div class="quiz-header">
              <h1>实现MySQL的横向扩展 - 交互式测验</h1>
              <p>检验你对文档内容的理解程度</p>
            </div>
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  {
    "question": "与升级单台服务器硬件的纵向扩展相比，横向扩展最核心的优势是什么？",
    "options": [
      "架构更简单，管理和维护成本更低。",
      "所有数据集中存储，更容易保证数据一致性。",
      "通过增加更多服务器节点来分散负载，从而提高系统的高可用性和弹性。",
      "初期投资成本更高，但性能提升是线性的。"
    ],
    "correctAnswerIndex": 2,
    "explanation": "横向扩展（Horizontal Scaling）的核心思想是通过增加更多的独立服务器来分担负载。这样做最显著的优势是，当某个节点发生故障时，其他节点仍然可以提供服务，从而大大提高了系统的整体可用性和容错能力。而纵向扩展因为依赖单台服务器，存在单点故障的风险。",
    "source": "文档中「横向扩展与纵向扩展的比较」部分的「4. 高可用性」",
    "hint": "思考一下，如果系统中只有一台超级服务器，它宕机了会发生什么？如果系统由10台普通服务器组成，其中一台宕机了又会怎样？"
  },
  {
    "question": "在MySQL主从复制的三种类型中，哪一种方案为了保证强数据一致性，对主库的写入性能影响最大？",
    "options": [
      "异步复制（Asynchronous Replication）",
      "半同步复制（Semi-synchronous Replication）",
      "同步复制（Synchronous Replication）",
      "延迟复制（Delayed Replication）"
    ],
    "correctAnswerIndex": 2,
    "explanation": "同步复制要求主数据库在提交事务前，必须等待所有从数据库都确认接收到数据变更。这个“等待所有从库确认”的过程会阻塞主库的写操作，直到所有从库都响应为止，因此虽然它保证了最高级别的数据一致性，但对写入性能的负面影响也是最大的。",
    "source": "文档中「主从复制」部分的「2. 复制类型」",
    "hint": "哪种复制方式要求主库承担的“等待责任”最重？"
  },
  {
    "question": "在实施“读写分离”架构时，开发者需要特别关注和处理的一个主要挑战是什么？",
    "options": [
      "写操作的压力无法被有效分摊。",
      "系统无法再进行水平扩展。",
      "主从数据库之间的数据复制延迟，可能导致应用读取到旧数据。",
      "数据库的配置变得过于简单，容易误操作。"
    ],
    "correctAnswerIndex": 2,
    "explanation": "读写分离依赖于主从复制机制。由于数据从主库复制到从库需要时间（即使很短），这个时间差被称为数据延迟。如果应用在主库写入数据后，立即去从库读取，就有可能因为数据还没同步过来而读到旧的、过时的数据。这是设计读写分离系统时必须考虑的一致性问题。",
    "source": "文档中「读写分离」部分的「5. 注意事项」",
    "hint": "文档中提到：“在写操作后，紧接着的读操作可能不会获得最新的数据。”"
  },
  {
    "question": "一个社交平台的数据库需要按用户ID进行数据分片，为了尽可能地让数据均匀分布在各个服务器上，避免“热点”数据问题，最适合采用哪种分片策略？",
    "options": [
      "基于范围的分片 (Range-based Sharding)",
      "基于哈希的分片 (Hash-based Sharding)",
      "基于列表的分片 (List-based Sharding)",
      "基于时间的分片 (Time-based Sharding)"
    ],
    "correctAnswerIndex": 1,
    "explanation": "基于哈希的分片通过对分片键（如此处的用户ID）进行哈希计算，然后根据哈希结果将数据路由到对应的分片。由于哈希算法的特性，即使是连续的用户ID（如新注册用户）也能被随机且均匀地分布到所有分片上，从而有效地避免了数据倾斜和热点问题。",
    "source": "文档中「数据分片」部分的「2. 分片的类型」",
    "hint": "哪种策略能将连续的输入值（如1, 2, 3, 4）映射到看似随机且分散的输出值？"
  },
  {
    "question": "在复杂的分布式数据库环境中，像MyCat或ShardingSphere这样的数据库中间件扮演的核心角色是什么？",
    "options": [
      "作为一种全新的数据库软件，直接替代MySQL进行数据存储。",
      "仅用于监控数据库的健康状态和性能指标。",
      "作为应用程序和数据库之间的抽象层，对应用透明地提供数据分片、读写分离等功能。",
      "主要负责数据库的物理备份和灾难恢复。"
    ],
    "correctAnswerIndex": 2,
    "explanation": "数据库中间件的核心价值在于“屏蔽底层复杂性”。它位于应用和实际的数据库集群之间，将多个物理数据库实例虚拟成一个单一的、逻辑上的数据库。应用程序只需与中间件交互，而数据分片、读写请求的路由、负载均衡等复杂操作都由中间件在后台处理，对应用程序是透明的。",
    "source": "文档中「数据库中间件」部分的「1. 概念」和「2. 核心功能」",
    "hint": "中间件就像一个“智能代理”，它位于应用和数据库之间，帮助应用处理复杂的请求分发。"
  },
  {
    "question": "MySQL主从复制机制能够工作的基石是什么？主数据库通过哪个组件来记录所有的数据变更操作？",
    "options": [
      "SQL线程 (SQL Thread)",
      "元数据管理 (Metadata Management)",
      "二进制日志 (Binlog)",
      "复制线程 (Replication Thread)"
    ],
    "correctAnswerIndex": 2,
    "explanation": "二进制日志（Binlog）是主从复制的核心。主数据库会将所有对数据库产生修改的操作（如INSERT, UPDATE, DELETE）以事件的形式记录在Binlog中。从数据库的复制线程会拉取这个日志，然后SQL线程再将日志中的事件在从库上重放，从而实现数据同步。",
    "source": "文档中「主从复制」部分的「3. 工作机制」",
    "hint": "主库需要有一个“账本”来记录自己做的所有修改，从库才能照着这个“账本”学习。"
  },
  {
    "question": "当数据库采用了数据分片（Sharding）之后，系统架构会面临的一个显著的技术挑战是？",
    "options": [
      "故障隔离能力变差，一个分片故障会导致整个系统瘫痪。",
      "系统的可扩展性受到限制，无法再增加新的数据库节点。",
      "单个数据库的写入压力会变得更大。",
      "处理需要跨多个分片聚合数据的查询（如JOIN或GROUP BY）变得非常复杂且性能可能较低。"
    ],
    "correctAnswerIndex": 3,
    "explanation": "数据分片虽然解决了单库容量和性能瓶颈，但也带来了新的复杂性。当一个查询需要的数据分散在不同的分片上时（例如，查询所有用户的订单总额），系统需要分别查询多个分片，然后将结果在中间件或应用层进行合并计算。这个过程远比在单个数据库中执行要复杂，并且网络开销和聚合逻辑会影响查询性能。",
    "source": "文档中「数据分片」部分的「5. 挑战与注意事项」",
    "hint": "思考一下，如果你的书籍按字母A-M和N-Z放在两个不同的书架上，要找出所有姓“Smith”的作者的书籍会有什么麻烦？"
  }
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                '<h3>错误率</h3>' +
                '<p>' + errorRate + '%</p>' +
                '</div>' +
                '<div class="score-card score-details">' +
                '<table>' +
                '<tr><td>正确</td><td>' + correctCount + '</td></tr>' +
                '<tr><td>错误</td><td>' + wrongCount + '</td></tr>' +
                '<tr><td>未答</td><td>' + skippedCount + '</td></tr>' +
                '</table>' +
                '</div>' +
                '</div>' +
                '<div class="report-actions">' +
                '<button id="review-btn">回顾测验</button>' +
                '<button class="primary" onclick="location.reload()">再试一次</button>' +
                '</div>' +
                '</div>';

            let reportEl = document.querySelector('.final-score-container');
            if (reportEl) {
                reportEl.remove();
            }
            quizContentEl.insertAdjacentHTML('beforeend', finalScoreHtml);
            document.getElementById('review-btn').addEventListener('click', reviewQuiz);
        }

        function reviewQuiz() {
            const reportEl = document.querySelector('.final-score-container');
            if (reportEl) {
                reportEl.remove();
            }

            document.querySelector('.quiz-body').style.display = 'block';
            document.getElementById('quiz-footer').style.display = 'flex';
            
            currentQuestionIndex = 0;
            loadQuestion();
            updateNavigationButtons(); // Ensure nav buttons are correctly displayed
        }

        // Event Delegation for options
        optionsListEl.addEventListener('click', (event) => {
            if (event.target && event.target.matches('li.option-item')) {
                // Check if the question has already been answered
                if (userAnswers[currentQuestionIndex] === null) {
                    const selectedIndex = parseInt(event.target.dataset.index, 10);
                    selectOption(selectedIndex);
                }
            }
        });

        prevBtn.addEventListener('click', goToPreviousQuestion);
        nextBtn.addEventListener('click', goToNextQuestion);
        hintBtn.addEventListener('click', showHint);
        
        // 初始加载
        loadQuestion();
      </script>
    </body>
    </html>
  